Land appearance inspecting device, and land appearance inspecting method

ABSTRACT

Land circle calculating means ( 7 ) calculates a land circle as an approximate circle from label information (S 6 ). Land circle accuracy-enhancing means ( 8 ) calculates again the land circle by changing a mask angle if land circle candidate information (S 7 ) obtained is improper, so as to enhance the accuracy of the land circle. AND operation means ( 11 ) carries out an AND operation of a land circle image (S 9 ) and a binary image (S 10 ) to create a land missing image (S 11 ). In-land binary means ( 12 ) calculates an in-land defect image (S 12 ) from an original image (S 4 ). OR operation means ( 13 ) carries out an OR operation of the in-land missing image (S 11 ) and the in-land defect image (S 12 ) to create a land defect image (S 13 ).

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a land appearance inspecting device andland appearance inspecting method for inspecting an appearance of anamorphous land whose shape is a circle with a protruding portion, suchas an LGA (Land Grid Array).

2. Description of the Related Art

Previously, as a land inspecting method, for example, in Japaneseunexamined patent publication no. 9-203620, a technique for inspecting abroken neck of a land has been disclosed. More specifically, a centerposition and radius of a through hole are calculated from image data,and image data of a region including a land is extracted on the basis ofthe center position and radius. And, on the basis of the extracted imagedata, an edge of a wiring pattern is resolved and extracted for eachpredetermined direction component as edge image data, and a shapecorresponding to a broken wiring portion is recognized on the basis of aplurality of the extracted edge image data, and a broken neck isdetermined on the basis of the recognized result.

Also, a technique has been disclosed in, for example, Japanese patentnos. 2502853 and 2502854, in which a wiring pattern and through holeportion are separated from image data, and the through hole portion ofthe wiring pattern is filled, while arbitrary amount expansionprocessing is applied to the separated through hole image, and logicaloperation is performed thereon with the filled binary image, whereby adiscrepancy portion is detected as a defect of a land portion of thethrough hole.

By the way, in integrated circuits, amorphous shape lands are arrangedat an equal pitch in a grid form on a package (PKG) reverse surface,which is called an LGA (Land Grid Array). The shape of a land in the LGAhas a feature of an amorphous circle with a protruding portion. Sincethe land has an aligned appearance, position angle inspection(inspection of coordinate position accuracy of a circular portion) isrequired for mounting, while it is important to detect a foreign body,flaw, and break on the land caused by a resistor failure, contact errorand the like.

However, the prior techniques are designed for inspection of the landdisposed on a general substrate, and consequently it is substantiallyimpossible to apply them to inspection of the reverse side of an ICcalled the LGA. Even if the prior land inspecting methods are applied toland inspection of the LGA, detected position accuracy is low, while nobreak (chip) can be detected in shape inspection.

SUMMARY OF THE INVENTION

In view of the foregoing, it is an object of the invention to provide aland appearance inspecting device and land appearance inspecting methodcapable of enhancing detection position accuracy of an amorphous landwhose shape is a circle with a protruding portion, while detecting aland break in shape inspection.

To solve the above-described problems, the invention of claim 1 ischaracterized by comprising: binarizing means, whereby an input imageread by scanning a measurement object pattern with a photoelectricconversion scanner is converted into a binarized image; land circlecalculating means for calculating a land circle which approximates aland shape from the binarized image converted by said binarizing means;and land circle accuracy enhancing means for calculating a land circlewhich minimizes an error of the land circle calculated by said landcircle calculating means; wherein land coordinates of an amorphous landwith a protrusion portion are detected with high accuracy, based on theland circle calculated by said land circle accuracy enhancing means.

Also, the invention of claim 2 is characterized by comprising: in theland appearance inspection device of claim 1, land defect detectionmeans for detecting a land internal defect and land circumferentialbreak, based on the land circle calculated by said land circle accuracyenhancing means; and determination means for determining land quality,based on the land internal defect and land circumferential break resultsdetected by said land defect detection means.

Also, the invention of claim 3 is characterized by comprising: in theland appearance inspection device of claim 1, land internal binarizationmeans for extracting a land internal defect, based on the land circlecalculated by said land circle calculating means.

Also, the invention of claim 4 is characterized by comprising: in theland appearance inspection device of claim 3, land external defectdetection means for detecting a land circumferential break, based on theland circle calculated by said land circle accuracy enhancing means andthe land internal defect extracted by said land internal binarizationmeans.

Also, the invention of claim 5 is characterized by comprising: in theland appearance inspection device of claim 1, land area calculationmeans for calculating land area based on the binarized image convertedby said binarizing means; land circle area calculation means forcalculating land circle area based on the land circle calculated by saidland circle accuracy enhancing means; and land protrusion portion areacalculation means for calculating a proportion of land protrusionportion area, based on the land area calculated by said land areacalculation means and the land circle area calculated by said landcircle area calculation means.

To solve the above-described problems, the invention of claim 6 ischaracterized by comprising the steps of: binarizing an input image readby scanning a measurement object pattern with a photoelectric conversionscanner; calculating a land circle which approximates a land shape fromthe binarized image; calculating a land circle which minimizes an errorof said land circle; and detecting land coordinates of an amorphous landwith a protrusion portion, based on said land circle.

Also, the invention of claim 7 is characterized in that: in the landappearance inspection method of claim 6, a land internal defect and landcircumferential break are detected, based on said land circle.

Also, the invention of claim 8 is characterized in that: in the landappearance inspection method of claim 6, a land internal defect isextracted, based on said land circle.

Also, the invention of claim 9 is characterized in that: in the landappearance inspection method of claim 8, a land circumferential break isdetected, based on said land circle and said land internal defect.

Also, the invention of claim 10 is characterized in that: in the landappearance inspection method of claim 6, land area is calculated basedon said binarized image; land circle area is calculated based on saidland circle; and a proportion of land protrusion portion area iscalculated based on said land area and said land circle area.

In this invention, a land circle which approximates a land shape from abinarized image converted by a binarizing means is calculated by a landcircle calculating means, and a land circle which minimizes an error ofthe land circle calculated by the land circle calculating means iscalculated by a land circle accuracy enhancing means. Accordingly, it ispossible to enhance detection position accuracy of a land with anamorphous shape of a circle with a protrusion portion, and to detect aland break in shape inspection.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing an overall system configuration inaccordance with an embodiment of the present invention.

FIG. 2 is a flow chart for explaining the overall operation of thepresent embodiment.

FIG. 3 is a flow chart for explaining the operation of the land circlecalculation processing for all lands.

FIG. 4 is a flow chart for explaining the operation of the land circlecalculation processing.

FIG. 5 is a flow chart for explaining the operation of the land defectdetection processing.

FIG. 6 is a pattern diagram for explaining the transformation fromXY-coordinates of land circumferential coordinates to an anglecoordinate θ.

FIG. 7 is a pattern diagram for explaining a protrusion direction.

FIG. 8 is a pattern diagram illustrating a radially divided region wherea centroid is centered.

FIG. 9 is a pattern diagram illustrating a land circle calculationresult.

FIG. 10 is a pattern diagram showing steps for enhancing land circleaccuracy.

FIG. 11 is a pattern diagram illustrating land internal defectdetection.

FIG. 12 is a block diagram showing a system configuration in accordancewith the first other embodiment of the present invention.

FIG. 13 is a block diagram showing a system configuration in accordancewith the second other embodiment of the present invention.

FIG. 14 is a block diagram showing a system configuration in accordancewith the third other embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERED EMBODIMENTS

Embodiments of the present invent ion will hereinafter be explained byuse of the accompanying drawings.

A. The Structure of the Embodiment

FIG. 1 is a block diagram showing an overall system configuration inaccordance with an embodiment of the present invention. In FIG. 1, aparameter input unit 1 inputs parameters required for inspection,converts them into a parameter signal S1 and feeds it to a parametermemory unit 2. The parameter memory unit 2 stores the parameter signalS1 and feeds it to a determination unit 16 as parameter information S2.

An image input unit 3 converts an LGA into an original image signal S3,and feeds it to an image memory unit 4. The image memory unit 4digitizes the original image signal S3 and stores it as an originalimage S4. If the original image S4 is larger than a land binarizationlevel of the parameter information S2, a land binarizing unit 5binarizes the original image S4 into “1”, or else “0”, and feeds it to alabeling unit 6 as a binary image S5. The labeling unit 6 performslabeling processing on the binary image S5, and feeds thecircumferential coordinates and centroids of all labels to a land circlecalculating unit 7 as XY-coordinate system label information S6. Theabove-mentioned labeling processing refers to processing of grouping aset of adjacent pixels evaluatable as one figure on the binary image,but, in the present embodiment, further involves calculating featuressuch as figure's area, length, circumferential length, circumferentialcoordinates, centroid and the like.

The land circle calculating unit 7 calculates a land circle from thelabel information S6 as an approximating circle, and feeds estimates,radius and center coordinates to a land circle accuracy enhancing unit 8as land circle nomination information S7. The land circle accuracyenhancing unit 8 evaluates whether the land circle nominationinformation S7 obtained is an adequate land circle or not, and, wheninadequate, alters a mask angle of the parameter information S2,re-calculates a land circle, and feeds it to a land circle imagepreparation unit 9 and a position angle calculating unit 15 as landcircle information S8.

The land circle image preparation unit 9 feeds to a logicalmultiplication unit 11 a land circle image S9, whose circle and insidenarrowed by offset of the parameter information S2 from the land circleinformation S8 are “1”, or else “0”. Also, if the original image S4 islarger than a land internal binarization level of the parameterinformation S2, a binarizing unit 10 binarizes the original image S4into “0”, or else “1”, prepares a binary image S10, and feeds it to thelogical multiplication unit 11. The logical multiplication unit 11 takeslogical multiplication of the land circle image S9 and the binary imageS10, prepares a land break image S11, and feeds it to a logical additionunit 13.

Also, if the label inside of the original image S4 is larger than a landinternal binarization level of the parameter information S2, a landinternal binarization unit 12 binarizes the label inside of the originalimage S4 into “0”, or else “1”, and feeds it to the logical additionunit 13 as a land internal defect image S12. The logical addition unit13 takes logical addition of the land break image S11 and the landinternal defect image S12, prepares a land defect image S13, and feedsit to a land defect labeling unit 14.

The land defect labeling unit 14 applies labeling processing to the landdefect image S3, and feeds it to the determination unit 16 as landdefect label information S14. The position angle calculating unit 15calculates position angle information S19 from the land circleinformation S8, and feeds it to the determination unit 16. The positionangle information S19 is information indicating deviation of an actualmeasured land position from a designed position. Specifically, actualmeasured land circle center coordinates (X, Y: included in the landcircle information S8) are compared with designed land positioncoordinates (X, Y) to which land overall position amendment (X, Y, θ) ismade, and an Euclid distance that is the shortest distance is calculatedfrom X-deviation and Y-deviation, and which is coordinate deviation,i.e. the position angle information S19.

The determination unit 16 determines the quality of the coordinatedeviation of the land on the basis of the position angle informationS19. Namely, if the coordinate deviation of the land is within atolerance (± tolerance value), a pass is evaluated. Also, thedetermination unit 16 determines the land defect label information S14by a land defect determination parameter of the parameter informationS2, prepares land defect information S15, and feeds it to a resultstorage unit 17. The result storage unit 17 stores the land defectinformation S15 as an inspection result, and feeds it to a result outputunit 18 as a land defect signal S16. The result output unit 18 outputsthe land defect signal S16 to a display, RS232C, network, etc.

B. The Operation of the Embodiment

Next, the overall operation of the present embodiment will be explainedin detail.

Here, FIG. 2 is a flow chart for explaining the overall operation of thepresent embodiment. First, an LGA image is obtained by the image inputunit 3, converted into an original image S4 and stored to the imagememory unit 4 (S10). Next, if the original image S4 is larger than aland binarization level of parameter information S2 stored in theparameter memory unit 2 beforehand by the parameter input unit 1, it isbinarization-processed by the land binarizing unit 5 into “1”, or else“0” (S12). Next, a binary image S5 obtained is labeling-processed by thelabeling unit 6 to calculate the circumferential coordinates andcentroids of individual labels as label information S6 (S14).

Next, a land circle that is an approximating circle is calculated fromthe label information S6 by the land circle calculating unit 7 to obtainland circle nomination information S7, and land circle information S8 iscalculated from the land circle nomination information S7 by the landcircle accuracy enhancing unit 8 (S16). Next, land defect detectionprocessing is performed for detecting a land internal defect and landcircumferential break (S18). Thereafter, based on a result obtained,quality determination is performed by the determination unit 16 (S20),and the result obtained is output by the result output unit 18 to adisplay, RS232C, network, etc. (S22).

Next, the operation of the above-mentioned land circle calculationprocessing in step S16 will be explained in detail. Here, FIG. 2 is aflow chart for explaining the operation of the land circle calculationprocessing for all lands. The land circle calculation is performed forindividual labels by using the circumferential coordinates and labelcentroid of each label information S6 calculated in the labeling unit 6.

First, whether the land circle calculation is performed or not for alllabels is evaluated (S30). If it has not been completed, aspreprocessing of the land circle calculation, as shown in FIG. 6, thecircumferential coordinates are transformed from an XY-coordinate systemto an angle coordinate θ (0≦θ<2π) in which a label centroid is centered(S32). Next, the land circle calculation is performed from a mask angleand division number of the angle coordinate θ and parameter informationS2 (S34). And, if the land circle calculation is performed for alllabels, it ends.

Next, the operation of the above-mentioned land circle calculationprocessing in step S34 will be explained further in detail. Here, FIG. 4is a flow chart for explaining the operation of the land circlecalculation processing. First, as shown in FIG. 8, the circumferentialangle coordinate θ is divided to set a mask range centered in a divisiondirection for each division direction (S40). The mask range is given bythe mask angle of parameter information S2, and circumferentialcoordinates with a circumferential angle coordinate θ belonging to thisrange are not used in the calculation of an approximating circle. Next,if it has not been calculated for all division directions,circumferential coordinates outside the mask range are selected from thecircumferential angle coordinate θ for each division direction to selectan approximating circle which minimizes an error and obtain estimatesthat represent center coordinates, radius and approximation accuracy(S44). This operation is performed for all division directions to set anapproximating circle which minimizes estimates to be a land circle (S46,S48, S50).

Here, a supplementary explanation is provided with respect to thecalculation processing of the approximating circle. The approximatingcircle is calculated basically by a least-squares method from thecircumferential coordinates and centroid obtained by the labelingprocessing. But since the shape of the land in the LGA has the featureof a circle with a protruding portion, if the least-squares method issimply applied to the entire circumferential length, only a circularportion cannot be detected. The best way is to apply the least-squaresmethod to a figure with the protruding portion excluded, but theprotrusion direction of the land in the LGA is irregular, and the numberof the lands is large, therefore holding as input information beforehand is an intricate and difficult task. Accordingly, in the presentembodiment, in order to allow an optimal approximating circle to bedetected irrespective of the position of the protrusion, a method isemployed in which a mask is applied to a portion in which the protrusionis assumed to be present, and an approximating circle is calculated withcircumferential coordinates except it. Because the portion in which theprotrusion is present is assumed to be in 8 directions in which the landcircular portion is centered, the approximating circle is calculated 8times individually by changing the mask application direction. Of the 8approximating circles obtained, the least error circle is set to be anoptimal approximating circle, and the direction of the mask which isthen applied is set to be a protrusion direction in which the protrusionportion is present.

In the above-described approximating circle calculation processing, inorder to apply a mask radially in 8 directions in which a centroid iscentered, XY-coordinates of the circumferential coordinates aretransformed into a θ-coordinate in which a centroid is centered. Themask is one of the parameter information input in the parameter inputunit beforehand as the mask angle. The significant feature of thiscalculation method is that the optimal approximating circle iscalculated, while at the same time the protrusion direction canautomatically be detected. That is, it is possible to detect the landcircular portion irrespective of the size and location of the protrudingportion, and the size of the circular portion.

By the way, in the event of the presence of a break due to a foreignbody, flaw or the like on the land, the shape of the land is distortedby some cause, which deteriorates land circle accuracy. In this case, asshown in FIG. 10, based on estimates, steps are taken to enhance landcircle accuracy. That is, the adequacy of the approximating circleobtained based on estimates is evaluated (S52), and if they are withinadequate ranges, determination is then made and the processing ends. Onthe other hand, if the estimates are outside the adequate ranges, a maskangle centered in a division direction is increased step by step (S58),the factor which distorts the shape of the land is eliminated, and landcircle calculation is re-performed (S40-S50). If the estimates arewithin the adequate ranges, a land circle is set, but even when the maskangle reaches a mask range limit illustrated in FIG. 10, if not withinthe adequate ranges, an approximating circle which minimizes theestimates calculated so far is selected and set as a land circle. Thedivision direction obtained is a protrusion direction, and is centercoordinates, radius and estimates as the land circle information.

FIG. 7 illustrates an example of setting a protrusion direction in thecase of division number “8”. Also, FIG. 9 illustrates a pattern diagramof a land circle calculation result example. Since the shape of the landhas the feature of a circular portion with a protruding portion, thecenter of the land circle basically does not coincide with the labelcentroid.

Next, the above-mentioned land defect detection processing in step S18will be explained in detail. Here, FIG. 5 is a flow chart for explainingthe operation of the land defect detection processing. Also, FIG. 11 isa pattern diagram for explaining a series of flow of land internaldefect detection processing. First, land internal binarization isperformed from an original image and label information (S60). That is,if smaller than a land internal binarization level, it is “1” or else“0”. Also, background except the land is “0”. Next, based on land circleinformation obtained, a land circle image is prepared (S62). That is, anarrow radius and inside of the land circle whose radius is narrowed byoffset of the parameter information S2 are “1”, or else “0”.

Next, the original image is binarized by the land internal binarizationlevel (S64). That is, if smaller than the land internal binarizationlevel, it is “1” or else “0”. Similar processing is performed also onbackground except the land. Next, logical multiplication of this binaryimage and land circle image is taken to extract a figure which is anomination of land break portion (S66). The figure obtained is a landbreak image. Next, logical addition of the land break image and the landinternal binary image is taken to obtain a land defect image (S68).Next, labeling processing is applied to the land defect image (S70), anddetermination is made to label information obtained to detect a landdefect (S72), and output (S74).

C. Other Embodiments

Next, other embodiments of the present invention will be explained.

C-1. The First Other Embodiment

FIG. 12 is a block diagram showing a configuration of the first otherembodiment of the present invention. Here, to portions corresponding tothose of FIG. 1, the same characters are added, and their explanationsomitted. The first other embodiment is characterized in that, bysubstituting an absolute difference unit 23 for the logical addition 13shown in FIG. 1, only a defect due to a break present in thecircumference of the LGA land is discriminated and detected as a landdefect image. If subtraction of a land internal defect image S12 from aland defect image S11 results in a minus, the absolute difference unit23 outputs “0” as a land defect image S13.

C-2. The Second Other Embodiment

FIG. 13 is a block diagram showing a configuration of the second otherembodiment of the present invention. Here, to portions corresponding tothose of FIG. 1 or FIG. 12, same characters are added and theirexplanations omitted. In the second other embodiment, by deleting theland circle image preparation unit 9, binarizing unit 10, logicalmultiplication unit 11, and logical addition unit 13 shown in FIG. 1,only a land internal defect can be discriminated and detected.

C-3. The Third Other Embodiment

FIG. 14 is a block diagram showing a configuration of the third otherembodiment of the present invention. Here, to portions corresponding tothose of FIG. 1, same characters are added and their explanationsomitted. In the third other embodiment, by adding an inspection unit 30to the configuration shown in FIG. 1, shades are inspected from anoriginal image S4 and label information S6, and fed to a determinationunit 16 as detection information S30. The determination unit 16determines the detection information S30 by determination parameters ofparameter information S2, and outputs land defect information S15. Also,in the inspection unit 30, from label information S6 and land circleinformation S8, {(label area−land circle area)/land circle area} iscalculated so that a proportion of protrusion portion area can bedetected and determined. Also, of the land circle information S8,estimates are a guide of whether a land shape is in the form ofdeviation from a land circle, so that the quality of the shape can bedetermined.

As explained above, according to the present invention, a land circlewhich approximates a land shape from a binarized image converted by abinarizing means is calculated by a land circle calculating means, and aland circle which minimizes an error of the land circle calculated bythe land circle calculating means is calculated by a land circleaccuracy enhancing means, so that land coordinates of an amorphous landwith a protrusion portion can be detected with high accuracy, which isan advantage.

Also, based on the land circle calculated by the land circle accuracyenhancing means, a land internal defect and land circumferential breakare detected by a land defect detection means, and based on the landinternal defect and land circumferential break results detected by theland defect detection means, land quality is determined by adetermination means, so that land defects due to a foreign body, flaw,break, etc., in a land with an amorphous shape of a circle with aprotrusion portion can be detected simultaneously, which is anadvantage.

Also, only a land internal defect is extracted by a land internalbinarization means, so that only a land internal foreign body and flawcan be discriminated from a land circumferential break and detected,which is an advantage.

Also, based on the land circle calculated by the land circle accuracyenhancing means and the land internal defect extracted by the landinternal binarization means, a land circumferential break is detected byland external defect detection, so that only the LGA landcircumferential break can be discriminated from the LGA land internaldefect due to a foreign body/flaw and detected, which is an advantage.

Also, based on the binarized image converted by the binarizing means,land area is calculated by a land area calculation means, and based onthe land circle calculated by the land circle accuracy enhancing means,land circle area is calculated by a land circle area calculation means,and based on the land area and the land circle area, a proportion ofland protrusion portion area is calculated by a land protrusion portionarea calculation means, so that land shape quality can be determined,based on protrusion portion area quality, which is an advantage.

1. A land appearance inspection device, comprising: binarizing means,whereby an input image read by scanning a measurement object patternwith a photoelectric conversion scanner is converted into a binarizedimage; land circle calculating means for calculating a land circle whichapproximates a land shape from the binarized image converted by saidbinarizing means; and land circle accuracy enhancing means forcalculating a land circle which minimizes an error of the land circlecalculated by said land circle calculating means; wherein landcoordinates of an amorphous land with a protrusion portion are detectedwith high accuracy, based on the land circle calculated by said landcircle accuracy enhancing means.
 2. A land appearance inspection deviceaccording to claim 1, further comprising: land defect detection meansfor detecting a land internal defect and land circumferential break,based on the land circle calculated by said land circle accuracyenhancing means; and determination means for determining land quality,based on the land internal defect and land circumferential break resultsdetected by said land defect detection means.
 3. A land appearanceinspection device according to claim 1, further comprising: landinternal binarization means for extracting a land internal defect, basedon the land circle calculated by said land circle calculating means. 4.A land appearance inspection device according to claim 3, furthercomprising: land external defect detection means for detecting a landcircumferential break, based on the land circle calculated by said landcircle accuracy enhancing means and the land internal defect extractedby said land internal binarization means.
 5. A land appearanceinspection device according to claim 1, further comprising: land areacalculation means for calculating land area based on the binarized imageconverted by said binarizing means; land circle area calculation meansfor calculating land circle area based on the land circle calculated bysaid land circle accuracy enhancing means; and land protrusion portionarea calculation means for calculating a proportion of land protrusionportion area, based on the land area calculated by said land areacalculation means and the land circle area calculated by said landcircle area calculation means.
 6. A land appearance inspection method,comprising the steps of: binarizing an input image read by scanning ameasurement object pattern with a photoelectric conversion scanner;calculating a land circle which approximates a land shape from thebinarized image; calculating a land circle which minimizes an error ofsaid land circle; and detecting land coordinates of an amorphous landwith a protrusion portion, based on said land circle.
 7. A landappearance inspection method according to claim 6, wherein a landinternal defect and land circumferential break are detected, based onsaid land circle.
 8. A land appearance inspection method according toclaim 6, wherein a land internal defect is extracted, based on said landcircle.
 9. A land appearance inspection method according to claim 8,wherein a land circumferential break is detected, based on said landcircle and said land internal defect.
 10. A land appearance inspectionmethod according to claim 6, wherein: land area is calculated based onsaid binarized image; land circle area is calculated based on said landcircle; and a proportion of land protrusion portion area is calculatedbased on said land area and said land circle area.